🎯 Data Analyst | Machine Learning | Engineering Background 📍 Barcelona, Spain
I specialize in analyzing datasets to generate actionable insights and support data-driven decision-making.
- Background in Project Engineering (Oil & Gas / Offshore Projects)
- MSc in Data Science & Machine Learning
- Experience with real-world operational, financial, and urban datasets
- Strong focus on turning data into business insights
- Urban data analysis using Open Data BCN and demographic data
- Feature engineering and consumption-per-capita metrics
- Exploratory and spatial analysis of district-level patterns
- Unsupervised learning (clustering) to segment urban consumption behavior
- Interactive visualization deployed with GitHub Pages
- Analysis of urban inequalities using Open Data BCN
- Machine Learning model (XGBoost, F1 ≈ 0.78)
- SHAP explainability for model interpretation
- Flask API for real-world application
- Financial data analysis and forecasting
- Trend and seasonality modeling
- Languages: Python, SQL
- Libraries: Pandas, NumPy, Scikit-learn, XGBoost, SHAP
- Data Visualization: Matplotlib, Seaborn, Power BI
- Other: Flask, Git, Data Analysis, Machine Learning
- LinkedIn: https://www.linkedin.com/in/ssilvacris/